Foundational Social Psychology Experiments (And Why Analysts Should Know Them) – Part 1 of 5
Foundational Social Psychology Experiments
(And Why Analysts Should Know Them) – Part 1 of 5
Digital Analytics is a relatively new field, and as such, we can learn a lot from other disciplines. This series of posts looks at some classic studies from social psychology, and what we analysts can learn from them.
Jump to an individual topic:
- The Magic Number 7 (or, 7 +/- 2)
- When The Facts Don’t Matter
- Confirmation Bias
- Conformity to the Norm
- Primacy and Recency Effects
- The Halo Effect
- The Bystander Effect (or “Diffusion of Responsibility”)
- Selection Attention
- False Consensus
- Homogeneity of the Outgroup
- The Hawthorne Effect
In 1956, George A. Miller conducted an experiment that found that the number of items a person can hold in working memory is seven, plus or minus two. However, all “items” are not created equal – our brain is able to “chunk” information to retain more. For example, if asked to remember seven words or even seven quotes, we can do so (we’re not limited to seven letters) because each word is an individual item or “chunk” of information. Similarly, we may be able to remember seven two-digit numbers, because each digit is not considered its own item.
Why this matters for analysts: This is critical to keep in mind as we are presenting data. Stephen Few argues that a dashboard must be confined to one page or screen. This is due to this limitation of working memory. You can’t expect people to look at a dashboard and draw conclusions about relationships between separate charts, tables, or numbers, while flipping back and forth constantly between pages, because this requires they retain too much information in working memory. Similarly, expecting stakeholders to recall and connect the dots between what you presented eleven slides ago is putting too great a pressure on working memory. We must work with people’s natural capabilities, and not against them.
In 1957, Leon Festinger studied a Doomsday cult who believed that aliens would rescue them from a coming flood. Unsurprisingly, no flood (nor aliens) eventuated. In their book, When Prophecy Fails, Festinger et al commented, “A man with a conviction is a hard man to change. Tell him you disagree and he turns away. Show him facts or figures and he questions your sources. Appeal to logic and he fails to see your point … Suppose that he is presented with evidence, unequivocal and undeniable evidence, that his belief is wrong: what will happen? The individual will frequently emerge, not only unshaken, but even more convinced of the truth of his beliefs than ever before.”
In a 1967 study by Brock & Balloun, subjects listened to several messages, but the recording was staticky. However, the subjects could press a button to clear up the static. They found that people selectively chose to listen to the message that affirmed their existing beliefs. For example, smokers chose to listen more closely when the content disputed a smoking-cancer link.
However, Chanel, Luchini, Massoni, Vergnaud (2010) found that if we are given an opportunity to discuss the evidence and exchange arguments with someone (rather than just reading the evidence and pondering it alone) we are more likely to change our minds in the face of opposing facts.
Why this matters for analysts: Even if your data seems self-evident, if it goes against what the business has known, thought, or believed for some time, you may need more data to support your contrary viewpoint. You may also want to allow for plenty of time for discussion, rather than simply sending out your findings, as those discussions are critical to getting buy-in for this new viewpoint.
More to come tomorrow.
What are your thoughts? Do these pivotal social psychology experiments help to explain some of the challenges you face with analyzing and presenting data?